Tech Lead, Backend - GraphAware Hume

About Neo4j

Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems.

It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community.

Intelligence that works.

Results that matter.

About Neo4j

Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems.

It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community.

Intelligence that works.

Results that matter.

Built to work everywhere and integrate with everything across every cloud for dynamic, personalized, and autonomous AI systems.

We deliver quicker results, contextual knowledge, and solutions that impact customers and employees across the business.

Our Vision

At Neo4j, we have always strived to help the world make sense of data.

As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships.

We created, drive and lead the graph database category, and we’re disrupting how organizations leverage their data to innovate and stay competitive.

The Role

We are aiming to hire someone in the the UK, Czechia or Italy.

Product Engineering at Graph Aware offers a unique opportunity to build real-world intelligence systems that matter.

• Build with purpose: Your code will help law enforcement and analysts save lives and protect communities through better data insight.
• Innovative tech: Work with knowledge graphs, workflow engines, LLMs, and graph-native UIs pushing the boundaries of data analytics.
• Shape the future: Contribute to product direction and technical vision alongside a senior engineering team.
• True autonomy: Own your work, from ideation to deployment.

Global mindset: Collaborate with a world-class team of engineers, data scientists, and product thinkers across Europe and beyond.

• Growth without bureaucracy: Develop your skills in a non-micromanaged, excellence-driven environment.
• What You Will Be Doing

As Tech Lead, you will own core parts of the platform layer of Graph Aware Hume, our graph-powered analytics platform — the foundations that cut across every development group and that every feature team builds on.

You'll be sought out across the organisation for technical guidance on graph architecture, and expected to anticipate issues at the product level before they surface.

Neo4j sits at the heart of the product, we need someone who goes beyond using it well, and actively tracks new features, tests them against real workloads, and identifies where they can move the product forward.

Working hands-on with Neo4j at the heart of the product, you will drive the architecture that lets us model, query, and scale the knowledge graphs our users depend on.

• Your Responsibilities Will Include
• Driving platform architecture, setting technical direction for the transversal foundations that feature teams across Hume build on, and shaping cross-cutting design decisions with the wider engineering group
• Owning our Neo4j strategy: actively tracking and hands-on testing of new releases and ecosystem tooling (GDS, APOC, etc.) to assess breaking changes, propose new product opportunities, and plan deliberate, scalable migrations.
• Optimizing Cypher queries and graph access patterns for latency, throughput, and scale
• Mentoring engineers and raising the team's technical bar (especially in Neo4j), without formal management authority
• Partner closely with Product Managers: to translate long-term product goals into scalable technical roadmaps
• Designing secure, scalable access control systems for mission-critical environments
• Building APIs for intuitive user interaction with complex data
• Orchestrating workflows to automate graph analytics, inference, and real-time insights
• What you must know already and be excited to grow further
• Deep, hands-on Neo4j expertise, including advanced Cypher query performance optimization, profiling, and deep familiarity with the broader Neo4j ecosystem (e. g., GDS, APOC, drivers).
• Modelled real domains as property graphs and can reason about nodes, relationships, labels, and properties as a first-class design activity (relational modelling with e. g.
• Postgre SQL is a plus)
• Track record of leading architecture and technical direction for a team or product area, not just contributing to decisions made by others
• Proven ability to drive consensus: across engineering teams for large-scale architectural changes.
• Proven experience in backend systems (8+ years) with exposure to large-scale, complex applications and cross-functional teams
• Fluency in Java (or a strong JVM background you can bring to a Java codebase), with a deep understanding of modern software engineering principles, including:
• Clean Architecture, Domain-Driven Design (DDD), and Test-Driven Development (TDD)
• Advanced debugging and profiling techniques,
• Writing composable, maintainable, and testable code
• Spring or similar frameworks with emphasis on building secure, modular, and scalable APIs
• Working knowledge of modern CI/CD pipelines, containerization (Docker), and automated deployment workflows
• Strong security mindset, with practical knowledge of secure software design and common vulnerabilities (e. g., OWASP)
• Comfortable with remote team collaboration, i. e. tools and practices for asynchronous communication
• Bonus Points For Familiarity With
• Knowledge graphs and Graph RAG: building knowledge graphs and grounding LLMs with graph-based retrieval (e. g. neo4j-graphrag, Lang Chain, Llama Index)
• Graph algorithms and analytics: (pathfinding, centrality, community detection) via Neo4j GDS, plus event-driven architectures, Kafka, or distributed systems
• Evolving large graph data models: over time: schema refactoring, migrations, and versioning as the domain grows
• Cloud-native development: observability, and performance tuning
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